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Johns Hopkins researchers to use machine learning to predict heart damage in COVID-19 victims

Natalia Trayanova | Via Johns Hopkins University | May 18, 2020

Johns Hopkins researchers recently received a $195,000 Rapid Response Research grant from the National Science Foundation to, using machine learning, identify which COVID-19 patients are at risk of adverse cardiac events such as heart failure, sustained abnormal heartbeats, heart attacks, cardiogenic shock and death.

Increasing evidence of COVID-19’s negative impacts on the cardiovascular system highlights a great need for identifying COVID-19 patients at risk for heart problems, the researchers say. However, no such predictive capabilities currently exist.

“This project will provide clinicians with early warning signs and ensure that resources are allocated to patients with the greatest need,” says Natalia Trayanova, the Murray B. Sachs Professor in the Department of Biomedical Engineering at The Johns Hopkins University Schools of Engineering and Medicine and the project’s principal investigator… Continue reading.

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